You might think that Terminator shows where we are today in terms of the level of AI. Although the explosive growth in information science and machine learning has led to an AI boom, we’re still very far from what the movies show.
Before listening to the below videos talking about how AI is helping humans, let’s try to understand what this is. There are many Artificial Intelligence definitions out there, but I’ll take the below one for a basic introduction:
AI is the field of study of intelligent agents: any system that perceives its environment and takes actions that maximize its chance of achieving its goals.Wikipedia
If we understand this definition, we can extract from it that:
- AI is not a technology, a robot, or a tool but a field of study instead
- It can be any system such as robots, software applications (chatbots)
- These intelligent agents perceive their environment (even if it’s partially)
- These intelligent agents want to achieve a set of goals (even if these are limited)
There’s an AI rule of thumb shared by Andrew NG, Co-Founder of Coursera, that might help you to understand what can be currently automated using Machine Learning:
If a typical person can do a mental task with less than one second of thought, we can probably automate it using AI either now or in the near future.Andrew NG
You might have heard in the news or through marketing campaigns that AI is everywhere and that this will take a lot of humans’ jobs. On a note aside, AI is already helping and teaching humans on how to become better and have a better life. Hear the below three people sharing their stories on how machine learning (or AI) is being used to help in different areas.
How AI can help shatter barriers to equality
Taking her personal life as an example, Jamila is sharing how AI is helping refugees and migrants find jobs and develop the necessary skills for this. AI might take away some jobs, but it’s also making amazing things for people that otherwise would be left behind:
How bad data keeps us from good AI
What happens when the algorithms get trained on biased data? Mazumdar showcases how spending less time on gathering and getting quality data can lead to AI making wrong decisions and predictions. What happens with AI ethics in this case?
Why we’re more honest with machines than people
From a funny story that happened in her life, Anne shares how machines get us to open up better than actual people. Chatbots, for instance, do not judge as humans do. Therefore, it’s easier to open ourselves to them – on health and other topics – making the interaction more honest and direct. These insights could lead to more honest interactions in our day-to-day lives.
Have you got more examples? Let me know in the comments!